Zooplankton salinity relationships in Suisun
Sam Bashevkin
8/26/2022
Load packages
require(dplyr)
require(zooper)
require(lubridate)
require(readr)
require(tidyr)
require(ggplot2)
require(sf)
require(readxl)
require(stringr)
require(mgcv)
require(purrr)
require(deltamapr)
require(scales)Load and wrangle data
zoop_data<-Zoopsynther(Data_type="Community", Sources=c("EMP", "STN", "20mm", "FMWT"), Time_consistency = TRUE)## [1] "These species have no relatives in their size class common to all datasets and have been removed from one or more size classes: Ostracoda Adult (Meso), Cumacea Adult (Meso), Annelida Adult (Meso), Gammarus Adult (Meso), Orientomysis aspera Adult (Meso), Chironomidae Larva (Meso), Insecta Larva (Meso)"Read in zoop mass conversions
zoop_mass_conversions<-read_excel("Data/SMSCG salinity modeling/Biomass conversions.xlsx", sheet="Micro and Meso-zooplankton")%>%
mutate(Taxname=case_when(Taxname=="Sinocalanus"~"Sinocalanus doerrii", # Change to help this match to zoop data
TRUE ~ Taxname),
Taxlifestage=paste(Taxname, Lifestage))%>%
select(Taxlifestage, CarbonWeight_ug)Read in zoop groupings
zoop_groups<-read_csv("Data/zoopcrosswalk2.csv", col_types=cols_only(Taxlifestage="c", IBMR="c"))%>%
distinct()Load Mysid biomass data
zoop_mysid<-read_excel("Data/1972-2020MysidBPUEMatrix.xlsx", # EMP
sheet="Mysid_BPUE_matrix_1972-2020", na = "NA",
col_types = c(rep("numeric", 4), "date", "text", "text", rep("text", 7), rep("numeric", 8)))%>%
select(Date=SampleDate, Station=StationNZ, BPUE=`Hyperacanthomysis longirostris`)%>% # Only select Hyperacanthomysis longirostris
mutate(Source="EMP")%>%
bind_rows(read_csv("Data/FMWT STN 2007to2019 Mysid BPUE.csv", # FMWT/STN
col_types=cols_only(Station="c", SampleDate="c", Project="c", `Hyperacanthomysis longirostris`="d"))%>%
rename(Date=SampleDate, Source=Project, BPUE=`Hyperacanthomysis longirostris`)%>% # Only select Hyperacanthomysis longirostris
mutate(Date=mdy(Date),
Station=recode(Station, MONT="Mont", HONK="Honk")))%>% #Get station names to match to main dataset
mutate(BPUE_mysid=BPUE*1000, # Convert to ug
Taxlifestage="Hyperacanthomysis longirostris Adult",
SampleID=paste(Source, Station, Date),
SizeClass="Macro")%>%
select(SampleID, Taxlifestage, SizeClass, BPUE_mysid)Start processing the zoop data
zoop_data_mass<-zoop_data%>%
mutate(Taxlifestage=str_remove(Taxlifestage, fixed("_UnID")))%>%
filter(
!(SizeClass=="Meso" & #eliminating species which are counted in meso and micro and retained better in the micro net from the meso calcs
Taxlifestage%in%c("Asplanchna Adult", "Copepoda Larva","Cyclopoida Juvenile", "Eurytemora Larva", "Harpacticoida Undifferentiated",
"Keratella Adult", "Limnoithona Adult", "Limnoithona Juvenile", "Limnoithona sinenesis Adult", "Limnoithona tetraspina
Adult", "Oithona Adult", "Oithona Juvenile", "Oithona davisae Adult", "Polyarthra Adult","Pseudodiaptomus Larva",
"Rotifera Adult", "Sinocalanus doerrii Larva", "Synchaeta Adult", "Synchaeta bicornis Adult", "Trichocerca Adult")) &
!(SizeClass=="Micro" &Taxlifestage%in%c("Cirripedia Larva", "Cyclopoida Adult", "Oithona similis")) & #removing categories better retained in meso net from micro net matrix
Order!="Amphipoda" & # Remove amphipods
(Order!="Mysida" | Taxlifestage=="Hyperacanthomysis longirostris Adult"))%>% #Only retain Hyperacanthomysis longirostris
mutate(Taxlifestage=recode(Taxlifestage, `Synchaeta bicornis Adult`="Synchaeta Adult", # Change some names to match to biomass conversion dataset
`Pseudodiaptomus Adult`="Pseudodiaptomus forbesi Adult",
`Acanthocyclops vernalis Adult`="Acanthocyclops Adult"))%>%
left_join(zoop_mass_conversions, by="Taxlifestage")%>% # Add biomass conversions
left_join(zoop_mysid, by=c("SampleID", "Taxlifestage", "SizeClass"))%>% # Add mysid biomass
left_join(zoop_groups, by="Taxlifestage")%>% # Add IBMR categories
mutate(BPUE=if_else(Taxlifestage=="Hyperacanthomysis longirostris Adult", BPUE_mysid, CPUE*CarbonWeight_ug))%>% # Create 1 BPUE variable
filter(!is.na(BPUE) & !is.na(Latitude) & !is.na(Longitude) & !is.na(SalSurf))%>% # Removes any data without BPUE, which is currently restricted to Decapod Larvae, and H. longirostris from STN. Also removes 20mm and EMP EZ stations without coordinates
group_by(IBMR)%>%
mutate(flag=if_else(all(c("Micro", "Meso")%in%SizeClass), "Remove", "Keep"))%>% # This and the next 2 lines are meant to ensure that all categories are consistent across the surveys. Since only EMP samples microzoops, only EMP data can be used for categories that include both micro and mesozoops.
ungroup()%>%
filter(!(flag=="Remove" & Source!="EMP"))%>%
select(SampleID, Station, Latitude, Longitude, SalSurf, Date, Year, IBMR, BPUE)%>%
group_by(across(-BPUE))%>%
summarise(BPUE=sum(BPUE), .groups="drop")%>% # Sum each IBMR categories
st_as_sf(coords=c("Longitude", "Latitude"), crs=4326)%>%
st_transform(crs=st_crs(deltamapr::R_DSIBM)) %>%
st_join(deltamapr::R_DSIBM %>%
select(SUBREGION)) %>%
st_drop_geometry() %>%
filter(SUBREGION %in% c("NW Suisun","SW Suisun","NE Suisun","SE Suisun","Confluence", "Suisun Marsh"))%>%
mutate(doy=yday(Date), #Day of year
Year_fac=factor(Year), # Factor year for model random effect
Station_fac=factor(Station), # Factor station for model random effect
across(c(SalSurf, doy), list(s=~(.x-mean(.x))/sd(.x))), # Center and standardize predictors
BPUE_log1p=log(BPUE+1)) # log1p transform BPUE for modelCheck sample size
zoop_sample_size <- zoop_data_mass %>% mutate(Month=month(Date)) %>%
group_by(SampleID,Year,Month,SUBREGION,Station) %>% summarise(BPUE=sum(BPUE)) %>% mutate(Samplesize=1) %>%
group_by(Year, Month, SUBREGION) %>% summarise(mean_BPUE=mean(BPUE),Samplesize=sum(Samplesize)) %>%
filter(Year>=1995)
ggplot(zoop_sample_size, aes(x=Year, y=Month, fill=Samplesize))+
geom_tile()+
scale_y_continuous(breaks=1:12, labels=month(1:12, label=T))+
scale_fill_viridis_c(breaks=c(1,5,10,15,20))+
facet_wrap(~SUBREGION)+
theme_bw()
All the remaining brackish regions have sufficient sample size with the exception of NE Suisun. As such, NE Suisun is to be combined with SE Suisun while the rest of the regions are to be analyzed on their own.
Create a new column with IBMR edited regions to accomodate combination of NE and SE Suisun regions.
zoop_data_mass$Subregion_edit<-ifelse(zoop_data_mass$SUBREGION=="NE Suisun"|zoop_data_mass$SUBREGION=="SE Suisun","East Suisun",zoop_data_mass$SUBREGION)Model
Prediction data
Set up prediction data for model
# Min year to start models
year_min<-2000
newdata_function<-function(region, data=zoop_data_mass){
data_filt<-data%>%
filter(Subregion_edit%in%region & Year >= year_min)
expand_grid(date=mdy(paste(1:12, 15, 2001, sep="/")), # The 15th of each month on a non-leap year
SalSurf=seq(round(quantile(data_filt$SalSurf, 0.025), 1),
round(quantile(data_filt$SalSurf, 0.975), 1), by=0.1))%>% # Salinity sequence nicely rounded to 1 decimal
mutate(Month=month(date),
doy=yday(date), # Day of year
SalSurf_s=(SalSurf-mean(data$SalSurf))/sd(data$SalSurf), # center and standardize salinity to match data
doy_s=(doy-mean(data$doy))/sd(data$doy))%>% # center and standardize doy to match data
select(Month, doy, doy_s, SalSurf, SalSurf_s)
}
newdata<-map(set_names(unique(zoop_data_mass$Subregion_edit)), newdata_function)Model fitting
model
sal_model<-function(group,region,new_data=newdata){
cat("<<<<<<<<<<<<<<<<<<<<<<< modeling", group, region, ">>>>>>>>>>>>>>>>>>>>>>>>>\n\n")
new_data<-new_data[[region]]
data<-filter(zoop_data_mass, IBMR==group & Subregion_edit==region & Year>=year_min)
par(mfrow=c(2,2))
if(length(unique(data$Station_fac))>1){
model<-gam(BPUE_log1p ~ te(SalSurf_s, doy_s, k=c(5,5), bs=c("cs", "cc")) +
s(Year_fac, bs="re") + s(Station_fac, bs="re"),
data=data,
method="REML")
random_effects<-c("s(Year_fac)", "s(Station_fac)")
}else{
model<-gam(BPUE_log1p ~ te(SalSurf_s, doy_s, k=c(5,5), bs=c("cs", "cc")) +
s(Year_fac, bs="re"),
data=data,
method="REML")
random_effects<-c("s(Year_fac)")
}
cat("-------------gam check-------------\n")
gam.check(model)
cat("\n\n-------------summary-------------\n")
print(summary(model))
sal<-predict(model, type="response", exclude=random_effects, newdata=new_data, se.fit=T, newdata.guaranteed=TRUE)%>%
as_tibble()%>%
mutate(across(everything(), as.vector))%>% # Make everything tidy
rename(fit=starts_with("fit"), se=starts_with("se.fit"))%>%
bind_cols(new_data%>% # Add covariate columns before these columns
select(-doy_s, -SalSurf_s),
.)
out<-list(model=model, sal=sal)
return(out)
}Apply model to all groups for the confluence region
model_factors<-expand_grid(IBMR=unique(zoop_data_mass$IBMR),
Subregion_edit=unique(zoop_data_mass$Subregion_edit))%>%
mutate(IBMR=set_names(IBMR, paste(IBMR, Subregion_edit)))
sal_models<-pmap(model_factors, function(IBMR, Subregion_edit) sal_model(IBMR, Subregion_edit))## <<<<<<<<<<<<<<<<<<<<<<< modeling acartela SW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 6 iterations.
## Gradient range [-0.0000008627989,0.0000007436512]
## (score 1364.484 & scale 2.255424).
## Hessian positive definite, eigenvalue range [1.577471,358.821].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.0 13.2 1.04 0.90
## s(Year_fac) 22.0 18.7 NA NA
## s(Station_fac) 5.0 3.7 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.0231 0.7743 3.904 0.000104 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 13.233 19 1291.567 <0.0000000000000002 ***
## s(Year_fac) 18.705 21 9.191 <0.0000000000000002 ***
## s(Station_fac) 3.702 4 13.250 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.559 Deviance explained = 58.1%
## -REML = 1364.5 Scale est. = 2.2554 n = 718
## <<<<<<<<<<<<<<<<<<<<<<< modeling acartela NW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 6 iterations.
## Gradient range [-0.00002037037,0.00001708752]
## (score 1670.069 & scale 2.085526).
## Hessian positive definite, eigenvalue range [1.239963,448.7965].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 15.41 0.95 0.02 *
## s(Year_fac) 22.00 19.81 NA NA
## s(Station_fac) 5.00 3.37 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.3517 0.3647 9.19 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 15.412 19 158.47 <0.0000000000000002 ***
## s(Year_fac) 19.810 21 17.81 <0.0000000000000002 ***
## s(Station_fac) 3.375 4 20.04 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.639 Deviance explained = 65.5%
## -REML = 1670.1 Scale est. = 2.0855 n = 898
## <<<<<<<<<<<<<<<<<<<<<<< modeling acartela East Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 6 iterations.
## Gradient range [-0.001994516,0.001678779]
## (score 3498.957 & scale 2.258205).
## Hessian positive definite, eigenvalue range [2.781527,932.1709].
## Model rank = 52 / 52
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 17.24 0.85 <0.0000000000000002 ***
## s(Year_fac) 22.00 20.44 NA NA
## s(Station_fac) 10.00 7.61 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.6115 0.3222 14.31 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 17.239 19 614.45 <0.0000000000000002 ***
## s(Year_fac) 20.441 21 35.45 <0.0000000000000002 ***
## s(Station_fac) 7.614 9 11.41 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.687 Deviance explained = 69.5%
## -REML = 3499 Scale est. = 2.2582 n = 1865
## <<<<<<<<<<<<<<<<<<<<<<< modeling acartela Confluence >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 7 iterations.
## Gradient range [-0.00009683616,0.00006015768]
## (score 3168.692 & scale 1.720377).
## Hessian positive definite, eigenvalue range [2.857675,909.1704].
## Model rank = 52 / 52
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 17.04 0.9 <0.0000000000000002 ***
## s(Year_fac) 22.00 20.27 NA NA
## s(Station_fac) 10.00 7.51 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.5163 0.2327 19.41 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 17.042 19 2320.69 <0.0000000000000002 ***
## s(Year_fac) 20.273 21 28.93 <0.0000000000000002 ***
## s(Station_fac) 7.508 9 14.94 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.816 Deviance explained = 82.1%
## -REML = 3168.7 Scale est. = 1.7204 n = 1819
## <<<<<<<<<<<<<<<<<<<<<<< modeling acartela Suisun Marsh >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 7 iterations.
## Gradient range [-0.000007833029,0.000006571361]
## (score 2510.554 & scale 1.57544).
## Hessian positive definite, eigenvalue range [1.409368,739.1935].
## Model rank = 50 / 50
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 15.81 0.95 <0.0000000000000002 ***
## s(Year_fac) 22.00 20.13 NA NA
## s(Station_fac) 8.00 5.72 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.9305 0.2142 18.35 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 15.809 19 1184.92 <0.0000000000000002 ***
## s(Year_fac) 20.125 21 23.51 <0.0000000000000002 ***
## s(Station_fac) 5.722 7 10.18 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.805 Deviance explained = 81%
## -REML = 2510.6 Scale est. = 1.5754 n = 1479
## <<<<<<<<<<<<<<<<<<<<<<< modeling daphnia SW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 5 iterations.
## Gradient range [-0.0000002663927,0.000000004633036]
## (score 958.1717 & scale 1.2462).
## Hessian positive definite, eigenvalue range [0.03635816,301.7651].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.000 12.707 0.91 0.015 *
## s(Year_fac) 22.000 15.287 NA NA
## s(Station_fac) 5.000 0.371 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.84806 0.09513 8.915 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 12.7067 19 85.368 <0.0000000000000002 ***
## s(Year_fac) 15.2867 21 2.792 <0.0000000000000002 ***
## s(Station_fac) 0.3706 4 0.114 0.286
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.626 Deviance explained = 64.4%
## -REML = 958.17 Scale est. = 1.2462 n = 604
## <<<<<<<<<<<<<<<<<<<<<<< modeling daphnia NW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 6 iterations.
## Gradient range [-0.00004392139,0.000004321613]
## (score 978.2129 & scale 1.328516).
## Hessian positive definite, eigenvalue range [0.3812971,300.2901].
## Model rank = 45 / 45
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.0 13.9 0.88 <0.0000000000000002 ***
## s(Year_fac) 22.0 15.6 NA NA
## s(Station_fac) 3.0 1.3 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.2991 0.1252 10.38 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 13.917 19 144.096 <0.0000000000000002 ***
## s(Year_fac) 15.621 21 3.110 <0.0000000000000002 ***
## s(Station_fac) 1.301 2 1.751 0.0725 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.707 Deviance explained = 72.2%
## -REML = 978.21 Scale est. = 1.3285 n = 601
## <<<<<<<<<<<<<<<<<<<<<<< modeling daphnia East Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 6 iterations.
## Gradient range [-0.0009480629,0.0003177903]
## (score 2220.249 & scale 1.587928).
## Hessian positive definite, eigenvalue range [0.5264055,654.1937].
## Model rank = 50 / 50
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 15.94 0.86 <0.0000000000000002 ***
## s(Year_fac) 22.00 19.04 NA NA
## s(Station_fac) 8.00 2.49 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.7823 0.1285 13.87 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 15.941 19 513.314 <0.0000000000000002 ***
## s(Year_fac) 19.038 21 10.614 <0.0000000000000002 ***
## s(Station_fac) 2.487 7 0.637 0.105
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.698 Deviance explained = 70.7%
## -REML = 2220.2 Scale est. = 1.5879 n = 1309
## <<<<<<<<<<<<<<<<<<<<<<< modeling daphnia Confluence >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 9 iterations.
## Gradient range [-0.00002608833,0.000008144597]
## (score 2635.918 & scale 2.406258).
## Hessian positive definite, eigenvalue range [0.9255191,692.1776].
## Model rank = 52 / 52
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 15.13 0.85 <0.0000000000000002 ***
## s(Year_fac) 22.00 19.01 NA NA
## s(Station_fac) 10.00 3.26 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.3452 0.1533 15.3 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 15.13 19 284.94 <0.0000000000000002 ***
## s(Year_fac) 19.01 21 11.19 <0.0000000000000002 ***
## s(Station_fac) 3.26 9 0.84 0.0329 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.578 Deviance explained = 58.9%
## -REML = 2635.9 Scale est. = 2.4063 n = 1385
## <<<<<<<<<<<<<<<<<<<<<<< modeling daphnia Suisun Marsh >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 8 iterations.
## Gradient range [-0.0002428841,0.00001931602]
## (score 1924.148 & scale 2.008222).
## Hessian positive definite, eigenvalue range [0.9076059,531.6783].
## Model rank = 48 / 48
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 12.93 0.94 0.02 *
## s(Year_fac) 22.00 16.76 NA NA
## s(Station_fac) 6.00 3.13 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.2671 0.1311 9.669 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 12.928 19 61.521 < 0.0000000000000002 ***
## s(Year_fac) 16.765 21 4.074 < 0.0000000000000002 ***
## s(Station_fac) 3.135 5 2.210 0.00706 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.488 Deviance explained = 50.4%
## -REML = 1924.1 Scale est. = 2.0082 n = 1064
## <<<<<<<<<<<<<<<<<<<<<<< modeling eurytem SW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 6 iterations.
## Gradient range [-0.0000231379,0.00001370843]
## (score 1189.543 & scale 2.549378).
## Hessian positive definite, eigenvalue range [1.413087,306.1333].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 12.17 0.95 0.045 *
## s(Year_fac) 22.00 8.54 NA NA
## s(Station_fac) 5.00 3.64 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.2232 0.7276 4.43 0.0000113 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 12.170 19 1604.185 < 0.0000000000000002 ***
## s(Year_fac) 8.537 21 0.717 0.0226 *
## s(Station_fac) 3.644 4 8.956 0.000000556 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.638 Deviance explained = 65.2%
## -REML = 1189.5 Scale est. = 2.5494 n = 613
## <<<<<<<<<<<<<<<<<<<<<<< modeling eurytem NW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 7 iterations.
## Gradient range [-0.0007984461,0.002096556]
## (score 1223.296 & scale 2.272916).
## Hessian positive definite, eigenvalue range [0.009782449,321.7709].
## Model rank = 46 / 46
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.000 15.224 1.05 0.94
## s(Year_fac) 22.000 14.976 NA NA
## s(Station_fac) 4.000 0.191 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.6258 0.1193 22.01 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 15.2236 19 83.35 <0.0000000000000002 ***
## s(Year_fac) 14.9762 21 2.57 <0.0000000000000002 ***
## s(Station_fac) 0.1913 3 0.07 0.333
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.623 Deviance explained = 64.1%
## -REML = 1223.3 Scale est. = 2.2729 n = 644
## <<<<<<<<<<<<<<<<<<<<<<< modeling eurytem East Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 7 iterations.
## Gradient range [-0.001088538,0.0006122747]
## (score 2559.596 & scale 2.287368).
## Hessian positive definite, eigenvalue range [1.250392,678.6741].
## Model rank = 50 / 50
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 18.11 0.8 <0.0000000000000002 ***
## s(Year_fac) 22.00 16.65 NA NA
## s(Station_fac) 8.00 4.94 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.0145 0.1317 22.9 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 18.113 19 220.674 < 0.0000000000000002 ***
## s(Year_fac) 16.654 21 3.569 < 0.0000000000000002 ***
## s(Station_fac) 4.942 7 2.758 0.000775 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.647 Deviance explained = 65.7%
## -REML = 2559.6 Scale est. = 2.2874 n = 1358
## <<<<<<<<<<<<<<<<<<<<<<< modeling eurytem Confluence >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 8 iterations.
## Gradient range [-0.0004815626,0.0002811514]
## (score 2648.62 & scale 2.42363).
## Hessian positive definite, eigenvalue range [1.350443,692.6672].
## Model rank = 52 / 52
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 16.81 0.76 <0.0000000000000002 ***
## s(Year_fac) 22.00 17.12 NA NA
## s(Station_fac) 10.00 4.82 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.9910 0.1281 23.35 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 16.809 19 155.451 < 0.0000000000000002 ***
## s(Year_fac) 17.120 21 4.653 < 0.0000000000000002 ***
## s(Station_fac) 4.822 9 1.865 0.00161 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.616 Deviance explained = 62.7%
## -REML = 2648.6 Scale est. = 2.4236 n = 1386
## <<<<<<<<<<<<<<<<<<<<<<< modeling eurytem Suisun Marsh >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 8 iterations.
## Gradient range [-0.00004639069,0.00003734725]
## (score 2299.299 & scale 2.46211).
## Hessian positive definite, eigenvalue range [1.4517,600.1833].
## Model rank = 50 / 50
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 14.23 0.76 <0.0000000000000002 ***
## s(Year_fac) 22.00 17.62 NA NA
## s(Station_fac) 8.00 4.62 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.2914 0.1951 22 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 14.228 19 200.360 <0.0000000000000002 ***
## s(Year_fac) 17.620 21 4.953 <0.0000000000000002 ***
## s(Station_fac) 4.624 7 8.852 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.667 Deviance explained = 67.7%
## -REML = 2299.3 Scale est. = 2.4621 n = 1201
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcalad SW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 5 iterations.
## Gradient range [-0.0002572946,0.00003618124]
## (score 1395.141 & scale 2.427992).
## Hessian positive definite, eigenvalue range [1.353422,364.2346].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 11.88 0.97 0.2
## s(Year_fac) 22.00 16.06 NA NA
## s(Station_fac) 5.00 2.82 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.6079 0.3297 20.04 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 11.885 19 119.352 <0.0000000000000002 ***
## s(Year_fac) 16.065 21 3.751 <0.0000000000000002 ***
## s(Station_fac) 2.819 4 20.190 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.419 Deviance explained = 44.4%
## -REML = 1395.1 Scale est. = 2.428 n = 729
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcalad NW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 6 iterations.
## Gradient range [-0.00023865,0.0002978932]
## (score 1553.35 & scale 1.666666).
## Hessian positive definite, eigenvalue range [0.4215564,454.0713].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 14.58 0.95 0.015 *
## s(Year_fac) 22.00 3.95 NA NA
## s(Station_fac) 5.00 2.72 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.1735 0.1674 36.88 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 14.576 19 46.585 <0.0000000000000002 ***
## s(Year_fac) 3.949 21 0.239 0.19
## s(Station_fac) 2.725 4 10.888 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.43 Deviance explained = 44.4%
## -REML = 1553.4 Scale est. = 1.6667 n = 909
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcalad East Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 6 iterations.
## Gradient range [-0.0009563874,0.0007150144]
## (score 3142.34 & scale 1.861551).
## Hessian positive definite, eigenvalue range [2.176514,892.6252].
## Model rank = 52 / 52
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 14.05 0.92 <0.0000000000000002 ***
## s(Year_fac) 22.00 17.46 NA NA
## s(Station_fac) 10.00 5.91 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.5775 0.1274 43.79 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 14.048 19 82.990 <0.0000000000000002 ***
## s(Year_fac) 17.460 21 4.973 <0.0000000000000002 ***
## s(Station_fac) 5.915 9 5.762 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.336 Deviance explained = 35%
## -REML = 3142.3 Scale est. = 1.8616 n = 1786
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcalad Confluence >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 8 iterations.
## Gradient range [-0.00001214517,0.00001013587]
## (score 3021.299 & scale 2.280475).
## Hessian positive definite, eigenvalue range [1.987953,802.6803].
## Model rank = 52 / 52
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 15.96 0.86 <0.0000000000000002 ***
## s(Year_fac) 22.00 19.80 NA NA
## s(Station_fac) 10.00 7.34 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.797 0.240 19.99 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 15.964 19 529.79 <0.0000000000000002 ***
## s(Year_fac) 19.802 21 17.90 <0.0000000000000002 ***
## s(Station_fac) 7.343 9 12.34 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.592 Deviance explained = 60.3%
## -REML = 3021.3 Scale est. = 2.2805 n = 1606
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcalad Suisun Marsh >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 10 iterations.
## Gradient range [-0.00007678109,0.00006071923]
## (score 2565.727 & scale 2.013629).
## Hessian positive definite, eigenvalue range [1.863386,706.1796].
## Model rank = 50 / 50
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 16.23 0.89 <0.0000000000000002 ***
## s(Year_fac) 22.00 18.29 NA NA
## s(Station_fac) 8.00 6.01 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.7579 0.2274 25.32 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 16.229 19 288.989 <0.0000000000000002 ***
## s(Year_fac) 18.293 21 7.878 <0.0000000000000002 ***
## s(Station_fac) 6.006 7 12.258 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.516 Deviance explained = 53%
## -REML = 2565.7 Scale est. = 2.0136 n = 1413
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcaljuv SW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 8 iterations.
## Gradient range [-0.0001800249,0.00006693502]
## (score 1147.796 & scale 1.167186).
## Hessian positive definite, eigenvalue range [1.123574,372.6134].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 12.52 0.99 0.34
## s(Year_fac) 22.00 8.82 NA NA
## s(Station_fac) 5.00 3.45 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 7.0294 0.3791 18.54 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 12.524 19 48.010 0.00179 **
## s(Year_fac) 8.820 21 0.724 0.02607 *
## s(Station_fac) 3.453 4 6.305 0.0000311 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.287 Deviance explained = 31.1%
## -REML = 1147.8 Scale est. = 1.1672 n = 746
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcaljuv NW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 7 iterations.
## Gradient range [-0.00000878828,0.000005536103]
## (score 1336.127 & scale 0.9687309).
## Hessian positive definite, eigenvalue range [0.1437059,459.7211].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.000 13.599 0.97 0.17
## s(Year_fac) 22.000 17.429 NA NA
## s(Station_fac) 5.000 0.934 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.4659 0.0891 72.57 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 13.599 19 43.539 <0.0000000000000002 ***
## s(Year_fac) 17.429 21 4.438 <0.0000000000000002 ***
## s(Station_fac) 0.934 4 0.383 0.194
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.339 Deviance explained = 36.2%
## -REML = 1336.1 Scale est. = 0.96873 n = 920
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcaljuv East Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 6 iterations.
## Gradient range [-0.001589764,0.001304635]
## (score 2751.792 & scale 1.009184).
## Hessian positive definite, eigenvalue range [2.190548,942.6308].
## Model rank = 52 / 52
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 16.76 0.84 <0.0000000000000002 ***
## s(Year_fac) 22.00 17.18 NA NA
## s(Station_fac) 10.00 6.91 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.5613 0.1172 55.96 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 16.760 19 138.233 <0.0000000000000002 ***
## s(Year_fac) 17.183 21 5.222 <0.0000000000000002 ***
## s(Station_fac) 6.907 9 7.246 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.416 Deviance explained = 42.8%
## -REML = 2751.8 Scale est. = 1.0092 n = 1886
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcaljuv Confluence >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 10 iterations.
## Gradient range [-0.0003469366,0.0002964759]
## (score 2502.853 & scale 0.8104333).
## Hessian positive definite, eigenvalue range [2.667065,924.1429].
## Model rank = 52 / 52
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 16.52 0.77 <0.0000000000000002 ***
## s(Year_fac) 22.00 18.32 NA NA
## s(Station_fac) 10.00 7.17 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.6926 0.1047 63.93 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 16.519 19 597.528 <0.0000000000000002 ***
## s(Year_fac) 18.319 21 7.584 <0.0000000000000002 ***
## s(Station_fac) 7.168 9 11.240 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.647 Deviance explained = 65.5%
## -REML = 2502.9 Scale est. = 0.81043 n = 1849
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcaljuv Suisun Marsh >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 8 iterations.
## Gradient range [-0.0000129569,0.000009089829]
## (score 2172.174 & scale 0.9594607).
## Hessian positive definite, eigenvalue range [1.860385,753.6472].
## Model rank = 50 / 50
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 16.30 0.88 <0.0000000000000002 ***
## s(Year_fac) 22.00 16.25 NA NA
## s(Station_fac) 8.00 6.55 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.7011 0.1916 34.98 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 16.305 19 92.370 <0.0000000000000002 ***
## s(Year_fac) 16.253 21 3.674 <0.0000000000000002 ***
## s(Station_fac) 6.547 7 44.101 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.391 Deviance explained = 40.7%
## -REML = 2172.2 Scale est. = 0.95946 n = 1508
## <<<<<<<<<<<<<<<<<<<<<<< modeling othclad SW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 5 iterations.
## Gradient range [-0.0000004305184,0.0000001698938]
## (score 967.7333 & scale 1.167392).
## Hessian positive definite, eigenvalue range [0.1565957,309.8204].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.000 11.754 0.96 0.14
## s(Year_fac) 22.000 17.840 NA NA
## s(Station_fac) 5.000 0.755 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.1666 0.1255 9.298 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 11.7540 19 193.911 <0.0000000000000002 ***
## s(Year_fac) 17.8397 21 5.380 <0.0000000000000002 ***
## s(Station_fac) 0.7546 4 0.317 0.187
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.708 Deviance explained = 72.2%
## -REML = 967.73 Scale est. = 1.1674 n = 620
## <<<<<<<<<<<<<<<<<<<<<<< modeling othclad NW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 5 iterations.
## Gradient range [-0.0002939791,0.0002133163]
## (score 994.1594 & scale 1.129614).
## Hessian positive definite, eigenvalue range [0.0908998,320.8165].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.000 12.983 0.87 0.005 **
## s(Year_fac) 22.000 17.631 NA NA
## s(Station_fac) 5.000 0.667 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.5283 0.1175 13.01 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 12.9833 19 285.282 <0.0000000000000002 ***
## s(Year_fac) 17.6306 21 5.067 <0.0000000000000002 ***
## s(Station_fac) 0.6673 4 0.244 0.233
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.762 Deviance explained = 77.4%
## -REML = 994.16 Scale est. = 1.1296 n = 642
## <<<<<<<<<<<<<<<<<<<<<<< modeling othclad East Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 7 iterations.
## Gradient range [-0.001230479,0.001020116]
## (score 2276.551 & scale 1.182822).
## Hessian positive definite, eigenvalue range [1.482809,732.6958].
## Model rank = 51 / 51
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 16.73 0.85 <0.0000000000000002 ***
## s(Year_fac) 22.00 19.81 NA NA
## s(Station_fac) 9.00 5.08 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.0466 0.1454 14.07 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 16.73 19 1268.214 < 0.0000000000000002 ***
## s(Year_fac) 19.81 21 17.853 < 0.0000000000000002 ***
## s(Station_fac) 5.08 8 3.036 0.0000935 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.764 Deviance explained = 77.1%
## -REML = 2276.6 Scale est. = 1.1828 n = 1466
## <<<<<<<<<<<<<<<<<<<<<<< modeling othclad Confluence >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 9 iterations.
## Gradient range [-0.000003926404,0.0000026836]
## (score 2716.839 & scale 1.357187).
## Hessian positive definite, eigenvalue range [1.776904,841.662].
## Model rank = 52 / 52
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 13.79 0.87 <0.0000000000000002 ***
## s(Year_fac) 22.00 19.72 NA NA
## s(Station_fac) 10.00 7.24 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.9868 0.1718 17.39 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 13.792 19 1190.80 <0.0000000000000002 ***
## s(Year_fac) 19.719 21 17.03 <0.0000000000000002 ***
## s(Station_fac) 7.237 9 16.57 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.681 Deviance explained = 68.9%
## -REML = 2716.8 Scale est. = 1.3572 n = 1684
## <<<<<<<<<<<<<<<<<<<<<<< modeling othclad Suisun Marsh >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 7 iterations.
## Gradient range [-0.00001218985,0.000004764209]
## (score 1976.119 & scale 1.332673).
## Hessian positive definite, eigenvalue range [1.673716,614.1956].
## Model rank = 50 / 50
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 12.98 0.95 0.025 *
## s(Year_fac) 22.00 19.04 NA NA
## s(Station_fac) 8.00 5.15 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.6001 0.1782 8.978 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 12.982 19 351.80 <0.0000000000000002 ***
## s(Year_fac) 19.037 21 10.60 <0.0000000000000002 ***
## s(Station_fac) 5.148 7 11.64 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.563 Deviance explained = 57.6%
## -REML = 1976.1 Scale est. = 1.3327 n = 1229
## <<<<<<<<<<<<<<<<<<<<<<< modeling pdiapfor SW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 7 iterations.
## Gradient range [-0.00004825721,0.00004025449]
## (score 1329.405 & scale 2.128419).
## Hessian positive definite, eigenvalue range [0.4176268,357.7591].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 11.67 0.98 0.27
## s(Year_fac) 22.00 16.78 NA NA
## s(Station_fac) 5.00 3.25 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.9977 0.4329 6.925 0.0000000000101 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 11.675 19 565.130 <0.0000000000000002 ***
## s(Year_fac) 16.777 21 3.951 <0.0000000000000002 ***
## s(Station_fac) 3.248 4 3.168 0.0142 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.574 Deviance explained = 59.3%
## -REML = 1329.4 Scale est. = 2.1284 n = 716
## <<<<<<<<<<<<<<<<<<<<<<< modeling pdiapfor NW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 8 iterations.
## Gradient range [-0.0005703755,0.0005119504]
## (score 1551.318 & scale 1.782146).
## Hessian positive definite, eigenvalue range [0.0001149825,441.2327].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.000000 11.587726 0.91 <0.0000000000000002 ***
## s(Year_fac) 22.000000 17.888654 NA NA
## s(Station_fac) 5.000000 0.000238 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.1835 0.1251 25.44 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 11.5877262 19 138.581 <0.0000000000000002 ***
## s(Year_fac) 17.8886541 21 5.524 <0.0000000000000002 ***
## s(Station_fac) 0.0002376 4 0.000 0.991
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.616 Deviance explained = 62.9%
## -REML = 1551.3 Scale est. = 1.7821 n = 883
## <<<<<<<<<<<<<<<<<<<<<<< modeling pdiapfor East Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 8 iterations.
## Gradient range [-0.000007808436,0.000007572253]
## (score 3382.853 & scale 2.089356).
## Hessian positive definite, eigenvalue range [1.574259,927.6431].
## Model rank = 52 / 52
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 13.71 0.78 <0.0000000000000002 ***
## s(Year_fac) 22.00 19.36 NA NA
## s(Station_fac) 10.00 6.81 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.1252 0.1913 21.56 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 13.707 19 794.558 <0.0000000000000002 ***
## s(Year_fac) 19.358 21 12.110 <0.0000000000000002 ***
## s(Station_fac) 6.813 9 9.976 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.671 Deviance explained = 67.8%
## -REML = 3382.9 Scale est. = 2.0894 n = 1856
## <<<<<<<<<<<<<<<<<<<<<<< modeling pdiapfor Confluence >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 14 iterations.
## Gradient range [-0.00004904667,0.00004633664]
## (score 3393.956 & scale 2.158042).
## Hessian positive definite, eigenvalue range [1.465866,922.6403].
## Model rank = 52 / 52
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 13.29 0.65 <0.0000000000000002 ***
## s(Year_fac) 22.00 19.38 NA NA
## s(Station_fac) 10.00 6.41 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.8498 0.1636 35.75 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 13.295 19 447.711 <0.0000000000000002 ***
## s(Year_fac) 19.383 21 12.192 <0.0000000000000002 ***
## s(Station_fac) 6.414 9 5.442 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.708 Deviance explained = 71.4%
## -REML = 3394 Scale est. = 2.158 n = 1846
## <<<<<<<<<<<<<<<<<<<<<<< modeling pdiapfor Suisun Marsh >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 9 iterations.
## Gradient range [-0.000005779316,0.000003814254]
## (score 2668.644 & scale 1.842018).
## Hessian positive definite, eigenvalue range [0.911504,751.1911].
## Model rank = 50 / 50
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 15.06 0.88 <0.0000000000000002 ***
## s(Year_fac) 22.00 20.07 NA NA
## s(Station_fac) 8.00 6.28 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.0426 0.2696 18.7 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 15.055 19 1729.08 <0.0000000000000002 ***
## s(Year_fac) 20.075 21 20.70 <0.0000000000000002 ***
## s(Station_fac) 6.284 7 22.22 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.698 Deviance explained = 70.6%
## -REML = 2668.6 Scale est. = 1.842 n = 1503
## <<<<<<<<<<<<<<<<<<<<<<< modeling allcopnaup SW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 7 iterations.
## Gradient range [-0.0002316378,0.0000446853]
## (score 490.1907 & scale 2.11028).
## Hessian positive definite, eigenvalue range [0.0002315783,131.3032].
## Model rank = 45 / 45
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.000000 8.356993 1.18 1
## s(Year_fac) 22.000000 10.999810 NA NA
## s(Station_fac) 3.000000 0.000553 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.0562 0.1331 7.934 0.0000000000000779 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 8.3569934 19 10.463 < 0.0000000000000002 ***
## s(Year_fac) 10.9998104 21 1.139 0.00247 **
## s(Station_fac) 0.0005527 2 0.000 0.82852
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.407 Deviance explained = 45.1%
## -REML = 490.19 Scale est. = 2.1103 n = 263
## <<<<<<<<<<<<<<<<<<<<<<< modeling allcopnaup NW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 5 iterations.
## Gradient range [-0.00001794221,-0.0000000669358]
## (score 507.6329 & scale 2.490058).
## Hessian positive definite, eigenvalue range [1.264975,128.07].
## Model rank = 42 / 42
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.0 10.1 0.94 0.13
## s(Year_fac) 22.0 15.2 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.5354 0.1931 7.953 0.0000000000000823 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 10.06 19 11.117 < 0.0000000000000002 ***
## s(Year_fac) 15.19 21 2.518 0.00000145 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.473 Deviance explained = 52.5%
## -REML = 507.63 Scale est. = 2.4901 n = 256
## <<<<<<<<<<<<<<<<<<<<<<< modeling allcopnaup East Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 7 iterations.
## Gradient range [-0.0001218762,0.00008344278]
## (score 1042.414 & scale 2.054096).
## Hessian positive definite, eigenvalue range [0.09903565,280.8695].
## Model rank = 46 / 46
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 13.02 0.91 0.005 **
## s(Year_fac) 22.00 17.86 NA NA
## s(Station_fac) 4.00 1.18 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.6774 0.1862 9.007 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 13.019 19 54.163 <0.0000000000000002 ***
## s(Year_fac) 17.865 21 5.753 <0.0000000000000002 ***
## s(Station_fac) 1.184 3 0.703 0.17
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.568 Deviance explained = 59.3%
## -REML = 1042.4 Scale est. = 2.0541 n = 562
## <<<<<<<<<<<<<<<<<<<<<<< modeling allcopnaup Confluence >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 9 iterations.
## Gradient range [-0.0001343447,0.0004613183]
## (score 1119.608 & scale 2.256841).
## Hessian positive definite, eigenvalue range [0.004593776,295.8296].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 11.00 0.88 <0.0000000000000002 ***
## s(Year_fac) 22.00 17.92 NA NA
## s(Station_fac) 5.00 0.11 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.7815 0.1673 10.65 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 10.9992 19 28.645 <0.0000000000000002 ***
## s(Year_fac) 17.9198 21 5.794 <0.0000000000000002 ***
## s(Station_fac) 0.1102 4 0.030 0.316
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.507 Deviance explained = 53.1%
## -REML = 1119.6 Scale est. = 2.2568 n = 592
## <<<<<<<<<<<<<<<<<<<<<<< modeling allcopnaup Suisun Marsh >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 9 iterations.
## Gradient range [-0.0004640216,0.0002288728]
## (score 1075.687 & scale 3.377358).
## Hessian positive definite, eigenvalue range [0.0004636947,255.4016].
## Model rank = 44 / 44
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00000 10.15265 0.91 <0.0000000000000002 ***
## s(Year_fac) 22.00000 18.59485 NA NA
## s(Station_fac) 2.00000 0.00139 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.758 0.248 7.089 0.00000000000485 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 10.152654 19 19.979 <0.0000000000000002 ***
## s(Year_fac) 18.594852 21 7.474 <0.0000000000000002 ***
## s(Station_fac) 0.001387 1 0.000 0.564
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.461 Deviance explained = 49.1%
## -REML = 1075.7 Scale est. = 3.3774 n = 511
## <<<<<<<<<<<<<<<<<<<<<<< modeling limno SW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 6 iterations.
## Gradient range [-0.00002968649,0.000001232434]
## (score 541.6089 & scale 2.906776).
## Hessian positive definite, eigenvalue range [0.00002968475,133.3596].
## Model rank = 45 / 45
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.0000000 7.6826839 0.82 <0.0000000000000002 ***
## s(Year_fac) 22.0000000 12.5507129 NA NA
## s(Station_fac) 3.0000000 0.0000932 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.5984 0.1683 33.27 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 7.6826840 19 7.485 < 0.0000000000000002 ***
## s(Year_fac) 12.5507129 21 1.490 0.000415 ***
## s(Station_fac) 0.0000932 2 0.000 0.659652
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.377 Deviance explained = 42.4%
## -REML = 541.61 Scale est. = 2.9068 n = 267
## <<<<<<<<<<<<<<<<<<<<<<< modeling limno NW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 5 iterations.
## Gradient range [-0.00000006008574,0.00000002717295]
## (score 487.0066 & scale 1.987343).
## Hessian positive definite, eigenvalue range [1.359051,129.5024].
## Model rank = 42 / 42
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.0 12.5 0.98 0.33
## s(Year_fac) 22.0 13.2 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.7549 0.1482 45.58 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 12.45 19 32.296 < 0.0000000000000002 ***
## s(Year_fac) 13.24 21 1.733 0.000104 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.678 Deviance explained = 71%
## -REML = 487.01 Scale est. = 1.9873 n = 259
## <<<<<<<<<<<<<<<<<<<<<<< modeling limno East Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 6 iterations.
## Gradient range [-0.0006348199,0.00005786304]
## (score 983.6937 & scale 1.643726).
## Hessian positive definite, eigenvalue range [0.9312309,280.8422].
## Model rank = 46 / 46
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 14.57 0.92 0.025 *
## s(Year_fac) 22.00 16.10 NA NA
## s(Station_fac) 4.00 2.36 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 7.0491 0.2286 30.84 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 14.575 19 86.759 < 0.0000000000000002 ***
## s(Year_fac) 16.102 21 3.373 < 0.0000000000000002 ***
## s(Station_fac) 2.359 3 6.766 0.000057 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.68 Deviance explained = 69.9%
## -REML = 983.69 Scale est. = 1.6437 n = 562
## <<<<<<<<<<<<<<<<<<<<<<< modeling limno Confluence >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 8 iterations.
## Gradient range [-0.0000004258262,0.0000002164561]
## (score 1093.584 & scale 1.914378).
## Hessian positive definite, eigenvalue range [1.122978,298.8587].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.0 15.0 0.99 0.42
## s(Year_fac) 22.0 17.3 NA NA
## s(Station_fac) 5.0 2.5 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.7636 0.2298 25.08 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 15.037 19 165.385 < 0.0000000000000002 ***
## s(Year_fac) 17.264 21 4.884 < 0.0000000000000002 ***
## s(Station_fac) 2.501 4 6.590 0.00000457 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.764 Deviance explained = 77.8%
## -REML = 1093.6 Scale est. = 1.9144 n = 598
## <<<<<<<<<<<<<<<<<<<<<<< modeling limno Suisun Marsh >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 7 iterations.
## Gradient range [-0.000001166027,0.00000108107]
## (score 950.2686 & scale 2.026855).
## Hessian positive definite, eigenvalue range [0.4761543,257.7166].
## Model rank = 44 / 44
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.000 14.382 0.95 0.1
## s(Year_fac) 22.000 10.732 NA NA
## s(Station_fac) 2.000 0.977 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.3167 0.4243 14.89 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 14.382 19 88.647 < 0.0000000000000002 ***
## s(Year_fac) 10.732 21 1.062 0.00346 **
## s(Station_fac) 0.977 1 42.760 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.731 Deviance explained = 74.5%
## -REML = 950.27 Scale est. = 2.0269 n = 516
## <<<<<<<<<<<<<<<<<<<<<<< modeling mysid SW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 6 iterations.
## Gradient range [-0.0001933873,0.0002357424]
## (score 665.2795 & scale 4.357742).
## Hessian positive definite, eigenvalue range [0.0001933676,147.5153].
## Model rank = 45 / 45
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.000000 9.186330 1.07 0.88
## s(Year_fac) 21.000000 15.828315 NA NA
## s(Station_fac) 4.000000 0.000859 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.3108 0.2774 15.54 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 9.1863304 19 22.208 <0.0000000000000002 ***
## s(Year_fac) 15.8283147 20 3.675 <0.0000000000000002 ***
## s(Station_fac) 0.0008593 3 0.000 0.529
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.551 Deviance explained = 58.9%
## -REML = 665.28 Scale est. = 4.3577 n = 295
## <<<<<<<<<<<<<<<<<<<<<<< modeling mysid NW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 7 iterations.
## Gradient range [-0.00000100028,0.0000008014995]
## (score 770.0372 & scale 3.602841).
## Hessian positive definite, eigenvalue range [0.2758678,179.3654].
## Model rank = 45 / 45
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 6.97 0.91 0.01 **
## s(Year_fac) 21.00 14.86 NA NA
## s(Station_fac) 4.00 2.95 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.564 1.141 3.999 0.0000784 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 6.975 19 11.653 0.0112 *
## s(Year_fac) 14.859 20 3.022 <0.0000000000000002 ***
## s(Station_fac) 2.948 3 107.229 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.513 Deviance explained = 54.6%
## -REML = 770.04 Scale est. = 3.6028 n = 359
## <<<<<<<<<<<<<<<<<<<<<<< modeling mysid East Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 5 iterations.
## Gradient range [-0.0005481093,0.0003275533]
## (score 1536.824 & scale 3.595509).
## Hessian positive definite, eigenvalue range [1.582611,359.7981].
## Model rank = 51 / 51
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 13.95 0.91 <0.0000000000000002 ***
## s(Year_fac) 21.00 16.13 NA NA
## s(Station_fac) 10.00 8.03 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.4520 0.4788 11.39 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 13.953 19 49.964 <0.0000000000000002 ***
## s(Year_fac) 16.131 20 5.252 <0.0000000000000002 ***
## s(Station_fac) 8.026 9 14.599 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.511 Deviance explained = 53.7%
## -REML = 1536.8 Scale est. = 3.5955 n = 720
## <<<<<<<<<<<<<<<<<<<<<<< modeling mysid Confluence >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 5 iterations.
## Gradient range [-0.0001386216,0.00007855902]
## (score 1432.811 & scale 3.158215).
## Hessian positive definite, eigenvalue range [2.015633,345.3202].
## Model rank = 50 / 50
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 14.80 0.94 0.03 *
## s(Year_fac) 21.00 16.84 NA NA
## s(Station_fac) 9.00 6.15 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.4107 0.3315 13.3 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 14.803 19 66.430 <0.0000000000000002 ***
## s(Year_fac) 16.837 20 5.458 <0.0000000000000002 ***
## s(Station_fac) 6.154 8 9.483 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.553 Deviance explained = 57.8%
## -REML = 1432.8 Scale est. = 3.1582 n = 691
## <<<<<<<<<<<<<<<<<<<<<<< modeling mysid Suisun Marsh >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 6 iterations.
## Gradient range [-0.00000009163887,0.00000006254805]
## (score 1240.961 & scale 3.302209).
## Hessian positive definite, eigenvalue range [1.772933,293.8917].
## Model rank = 48 / 48
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 14.46 0.93 0.015 *
## s(Year_fac) 21.00 17.82 NA NA
## s(Station_fac) 7.00 5.37 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.4655 0.6154 8.881 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 14.456 19 46.69 <0.0000000000000002 ***
## s(Year_fac) 17.818 20 7.94 <0.0000000000000002 ***
## s(Station_fac) 5.366 6 15.32 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.467 Deviance explained = 50.1%
## -REML = 1241 Scale est. = 3.3022 n = 588
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcyc SW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 8 iterations.
## Gradient range [-0.00007556176,0.00009483017]
## (score 509.2612 & scale 2.433443).
## Hessian positive definite, eigenvalue range [0.4394374,133.0907].
## Model rank = 45 / 45
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 5.83 1.01 0.47
## s(Year_fac) 22.00 5.38 NA NA
## s(Station_fac) 3.00 1.42 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.1753 0.6861 11.92 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 5.834 19 2.595 0.0000139 ***
## s(Year_fac) 5.380 21 0.341 0.1533
## s(Station_fac) 1.425 2 2.575 0.0286 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.18 Deviance explained = 21.9%
## -REML = 509.26 Scale est. = 2.4334 n = 267
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcyc NW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 5 iterations.
## Gradient range [-0.00000211291,0.0000001664891]
## (score 439.2156 & scale 1.385914).
## Hessian positive definite, eigenvalue range [0.9753164,129.5308].
## Model rank = 42 / 42
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.0 11.5 0.95 0.24
## s(Year_fac) 22.0 14.1 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.8233 0.1317 74.61 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 11.54 19 18.611 < 0.0000000000000002 ***
## s(Year_fac) 14.13 21 2.091 0.0000126 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.563 Deviance explained = 60.6%
## -REML = 439.22 Scale est. = 1.3859 n = 259
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcyc East Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 7 iterations.
## Gradient range [-0.000007037802,0.000005540019]
## (score 734.259 & scale 0.6699743).
## Hessian positive definite, eigenvalue range [0.676424,280.8599].
## Model rank = 46 / 46
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 14.62 0.85 <0.0000000000000002 ***
## s(Year_fac) 22.00 16.56 NA NA
## s(Station_fac) 4.00 2.13 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.4686 0.1291 73.33 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 14.62 19 129.269 < 0.0000000000000002 ***
## s(Year_fac) 16.56 21 3.941 < 0.0000000000000002 ***
## s(Station_fac) 2.13 3 5.055 0.000401 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.729 Deviance explained = 74.5%
## -REML = 734.26 Scale est. = 0.66997 n = 562
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcyc Confluence >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 6 iterations.
## Gradient range [-0.00001953905,0.000009775127]
## (score 1065.213 & scale 1.828141).
## Hessian positive definite, eigenvalue range [0.5511101,298.7089].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 14.05 1 0.46
## s(Year_fac) 22.00 12.05 NA NA
## s(Station_fac) 5.00 1.71 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.5017 0.1333 63.79 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 14.045 19 59.633 < 0.0000000000000002 ***
## s(Year_fac) 12.050 21 1.372 0.000549 ***
## s(Station_fac) 1.709 4 1.512 0.019549 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.616 Deviance explained = 63.4%
## -REML = 1065.2 Scale est. = 1.8281 n = 598
## <<<<<<<<<<<<<<<<<<<<<<< modeling othcyc Suisun Marsh >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 8 iterations.
## Gradient range [-0.0000003281669,0.0000002622332]
## (score 807.4669 & scale 1.179061).
## Hessian positive definite, eigenvalue range [0.4788483,257.6963].
## Model rank = 44 / 44
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 13.62 0.94 0.14
## s(Year_fac) 22.00 10.31 NA NA
## s(Station_fac) 2.00 0.98 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.5531 0.3452 27.68 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 13.6227 19 43.807 < 0.0000000000000002 ***
## s(Year_fac) 10.3110 21 0.952 0.00749 **
## s(Station_fac) 0.9799 1 49.083 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.592 Deviance explained = 61.2%
## -REML = 807.47 Scale est. = 1.1791 n = 516
## <<<<<<<<<<<<<<<<<<<<<<< modeling other SW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 7 iterations.
## Gradient range [-0.0001670581,0.0002365661]
## (score 534.6529 & scale 2.832547).
## Hessian positive definite, eigenvalue range [0.0001670419,131.5291].
## Model rank = 45 / 45
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.000000 8.317430 0.92 0.1
## s(Year_fac) 22.000000 15.272562 NA NA
## s(Station_fac) 3.000000 0.000808 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.8523 0.2061 33.26 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 8.3174305 19 3.025 0.0012 **
## s(Year_fac) 15.2725622 21 2.726 <0.0000000000000002 ***
## s(Station_fac) 0.0008082 2 0.000 0.5165
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.276 Deviance explained = 34.1%
## -REML = 534.65 Scale est. = 2.8325 n = 263
## <<<<<<<<<<<<<<<<<<<<<<< modeling other NW Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 8 iterations.
## Gradient range [-0.000002813325,0.000001070138]
## (score 563.051 & scale 4.169416).
## Hessian positive definite, eigenvalue range [0.3519045,127.8435].
## Model rank = 42 / 42
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 6.18 0.95 0.15
## s(Year_fac) 22.00 12.32 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.0799 0.2012 30.22 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 6.176 19 2.742 0.00000307 ***
## s(Year_fac) 12.323 21 1.435 0.000569 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.242 Deviance explained = 29.7%
## -REML = 563.05 Scale est. = 4.1694 n = 256
## <<<<<<<<<<<<<<<<<<<<<<< modeling other East Suisun >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 10 iterations.
## Gradient range [-0.0002368956,0.00006329163]
## (score 1181.35 & scale 3.458064).
## Hessian positive definite, eigenvalue range [0.3111446,280.782].
## Model rank = 46 / 46
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00 12.83 0.85 <0.0000000000000002 ***
## s(Year_fac) 22.00 15.07 NA NA
## s(Station_fac) 4.00 1.58 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.7462 0.2165 26.55 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 12.828 19 9.760 < 0.0000000000000002 ***
## s(Year_fac) 15.065 21 2.427 0.00000146 ***
## s(Station_fac) 1.583 3 1.673 0.0361 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.277 Deviance explained = 31.5%
## -REML = 1181.4 Scale est. = 3.4581 n = 562
## <<<<<<<<<<<<<<<<<<<<<<< modeling other Confluence >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 9 iterations.
## Gradient range [-0.0007093988,0.00006341095]
## (score 1225.46 & scale 3.157403).
## Hessian positive definite, eigenvalue range [0.0007088225,295.8561].
## Model rank = 47 / 47
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.00000 13.75261 0.88 <0.0000000000000002 ***
## s(Year_fac) 22.00000 17.83492 NA NA
## s(Station_fac) 5.00000 0.00155 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.457 0.195 27.99 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 13.752606 19 15.942 <0.0000000000000002 ***
## s(Year_fac) 17.834917 21 4.874 <0.0000000000000002 ***
## s(Station_fac) 0.001545 4 0.000 0.957
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.374 Deviance explained = 40.7%
## -REML = 1225.5 Scale est. = 3.1574 n = 592
## <<<<<<<<<<<<<<<<<<<<<<< modeling other Suisun Marsh >>>>>>>>>>>>>>>>>>>>>>>>>
##
## -------------gam check-------------
##
## Method: REML Optimizer: outer newton
## full convergence after 9 iterations.
## Gradient range [-0.0001598758,0.0002345354]
## (score 1084.387 & scale 3.560059).
## Hessian positive definite, eigenvalue range [0.002762813,255.3373].
## Model rank = 44 / 44
##
## Basis dimension (k) checking results. Low p-value (k-index<1) may
## indicate that k is too low, especially if edf is close to k'.
##
## k' edf k-index p-value
## te(SalSurf_s,doy_s) 19.0000 11.9129 1.05 0.88
## s(Year_fac) 22.0000 16.3017 NA NA
## s(Station_fac) 2.0000 0.0737 NA NA
##
##
## -------------summary-------------
##
## Family: gaussian
## Link function: identity
##
## Formula:
## BPUE_log1p ~ te(SalSurf_s, doy_s, k = c(5, 5), bs = c("cs", "cc")) +
## s(Year_fac, bs = "re") + s(Station_fac, bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.7214 0.1834 31.19 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df F p-value
## te(SalSurf_s,doy_s) 11.91288 19 11.749 <0.0000000000000002 ***
## s(Year_fac) 16.30174 21 3.443 <0.0000000000000002 ***
## s(Station_fac) 0.07371 1 0.079 0.299
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.36 Deviance explained = 39.6%
## -REML = 1084.4 Scale est. = 3.5601 n = 511Extract salinity conversions
sal_conversions<-map_dfr(sal_models, ~.x[["sal"]], .id = "IBMR_region")%>%
mutate(IBMR=sapply(IBMR_region, function(x) str_split(x, " ", n=2)[[1]][1]),
Region=factor(sapply(IBMR_region, function(x) str_split(x, " ", n=2)[[1]][2]), levels=c("Confluence", "Suisun Marsh", "East Suisun", "NW Suisun", "SW Suisun")),
Month=as.integer(Month))
str(sal_conversions)## tibble [91,584 × 8] (S3: tbl_df/tbl/data.frame)
## $ IBMR_region: chr [1:91584] "acartela SW Suisun" "acartela SW Suisun" "acartela SW Suisun" "acartela SW Suisun" ...
## $ Month : int [1:91584] 1 1 1 1 1 1 1 1 1 1 ...
## $ doy : num [1:91584] 15 15 15 15 15 15 15 15 15 15 ...
## $ SalSurf : num [1:91584] 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 ...
## $ fit : num [1:91584] 4.7 4.72 4.73 4.75 4.77 ...
## $ se : num [1:91584] 1.05 1.04 1.03 1.02 1.01 ...
## $ IBMR : Named chr [1:91584] "acartela" "acartela" "acartela" "acartela" ...
## ..- attr(*, "names")= chr [1:91584] "acartela SW Suisun" "acartela SW Suisun" "acartela SW Suisun" "acartela SW Suisun" ...
## $ Region : Factor w/ 5 levels "Confluence","Suisun Marsh",..: 5 5 5 5 5 5 5 5 5 5 ...
## ..- attr(*, "names")= chr [1:91584] "acartela SW Suisun" "acartela SW Suisun" "acartela SW Suisun" "acartela SW Suisun" ...plot salinity conversions
ggplot(sal_conversions, aes(x=SalSurf, y=fit, ymin=fit-se, ymax=fit+se, fill=IBMR))+
geom_ribbon(alpha=0.4)+
ylab("fit (log scale)")+
facet_grid(Region~Month)+
scale_fill_viridis_d()+
theme_bw()
Apply model
Load in SMSCG modeled salinity
modeled_sal<-read_csv("Data/CSAMP_DS_SDM_salinity_scenarios.csv",
col_types = cols_only(region="c", year="i", month="i",
sal_base="d", sal_fallX2_hi="d", sal_fallX2_low="d",
sal_sumX2_hi="d", sal_sumX2_low ="d", sal_SMSCG="d"))%>%
mutate(across(starts_with("sal_"), ~if_else(is.na(.x), sal_base, .x)))%>%
filter(region%in%unique(zoop_data_mass$SUBREGION))%>%
mutate(region=factor(region, levels=c("Confluence", "Suisun Marsh", "NE Suisun", "SE Suisun", "NW Suisun", "SW Suisun")))%>%
pivot_longer(cols=starts_with("sal_"), names_to="Scenario", values_to="Salinity")%>% # Prepare data for easier plotting
mutate(Scenario=factor(Scenario,
levels=c("sal_base","sal_fallX2_hi","sal_fallX2_low","sal_sumX2_hi","sal_sumX2_low","sal_SMSCG")))%>%
mutate(Salinity=round(Salinity, 1))Plot SMSCG modeled salinity
ggplot(modeled_sal,
aes(x=year, y=Salinity, color=Scenario))+
geom_line()+
scale_color_viridis_d()+
facet_grid(region ~ month(month, label=T))+
theme_bw()+
theme(legend.position = "bottom", axis.text.x=element_text(angle=45, hjust=1))
salinity conversion function
zoop_saladjusted<-modeled_sal%>%
mutate(Salinity=as.character(Salinity),
IBMR=unique(model_factors$IBMR)[1])%>%
complete(region, year, month, Scenario, IBMR=unique(model_factors$IBMR))%>%
group_by(region, year, month, Scenario)%>%
mutate(Salinity=na.exclude(Salinity),
region2=if_else(region%in%c("NE Suisun", "SE Suisun"), "East Suisun", as.character(region)))%>%
left_join(sal_conversions%>%
select(Region, Month, IBMR, SalSurf, fit)%>%
mutate(SalSurf=as.character(SalSurf)),
by=c("region2"="Region",
"month"="Month",
"Salinity"="SalSurf",
"IBMR"="IBMR"))%>%
select(-Salinity, -region2)%>%
mutate(fit=exp(fit)-1)%>%
pivot_wider(names_from="Scenario", values_from="fit")%>%
mutate(across(starts_with("sal_"), ~(.x-sal_base)/sal_base))Plot the missing model results resulting from out-of-range salinity values in the inputs
ggplot(zoop_saladjusted%>%
filter(IBMR=="acartela")%>%
pivot_longer(cols=starts_with("sal_"), names_to="Scenario", values_to="zoop_change"),
aes(x=year, y=Scenario, fill=is.na(zoop_change)))+
geom_tile()+
scale_fill_viridis_d(name="Are the model results missing due to out-of-range salinity values?")+
facet_grid(region ~ month(month, label=T))+
theme_bw()+
theme(legend.position = "bottom", axis.text.x=element_text(angle=45, hjust=1))
Plot the result
Create some plotting functions
neglop1p<-trans_new("neglop1p", transform=function(x) sign(x)*log(abs(x)+1), inverse=function(x) sign(x)*(exp(abs(x))-1))
plot_scenario_result <- function(scenario) {
ggplot(zoop_saladjusted,
aes(x=year, y=.data[[scenario]], color=IBMR))+
geom_point()+
scale_color_viridis_d()+
scale_y_continuous(trans=neglop1p, breaks=c(-1000, -100, -10, -1, 0, 1, 10, 100, 1000))+
ylab("Proportional change in zooplankton biomass (log scale)")+
facet_grid(region ~ month(month, label=T))+
theme_bw()+
theme(legend.position = "bottom", axis.text.x=element_text(angle=45, hjust=1))
}# Create plots for each Parameter
scenario_result_plots <- tibble(Scenario=unique(modeled_sal$Scenario)[-1])%>%
mutate(plot=map(as.character(unique(modeled_sal$Scenario))[-1], plot_scenario_result))Result plots
sal_fallX2_hi
## Warning: Removed 636 rows containing missing values (geom_point).
sal_fallX2_low
## Warning: Removed 108 rows containing missing values (geom_point).
sal_sumX2_hi
## Warning: Removed 132 rows containing missing values (geom_point).
sal_sumX2_low
## Warning: Removed 132 rows containing missing values (geom_point).
sal_SMSCG
## Warning: Removed 108 rows containing missing values (geom_point).